· Ong Wei Juin · documentation · 5 min read
Case Study: Unlocking Market Insights and Higher Conversions for a Leading Digital Property Platform
A leading digital property platform had its market, sales, and inventory data trapped in silos. See how our Data Engineering team built a scalable Data Lakehouse on AWS/Snowflake, enabling rich Analytics views and deploying an LLM-driven fuzzy search tool. This transformation eliminated friction, provided crucial market insights, and significantly increased user conversion rates.
In the highly competitive digital property market, speed and data integrity are everything. A platformâs success hinges on two factors: the accuracy of its market data and the ease with which a user can find their ideal property. Our client, a leading digital property platform, was struggling on both fronts due to a complex, siloed data ecosystem.
This project was a comprehensive transformation, leveraging the full spectrum of Data Engineering, Data Analytics, and AI/Data Science capabilities to centralize the platformâs core data and integrate a cutting-edge search experience.
The Summary (TL;DR)
**The Client: **A prominent digital property platform managing thousands of listings and millions of users across several key markets.
**The Challenge: **Data was siloed across systems (Inventory, CRM, Finance), resulting in slow, inaccurate market analysis and a poor user experience due to a rigid, fault-prone search bar.
**The Solution: **Polar Packet built a Data Lakehouse powered by Snowflake and AWS to centralize all critical data. We then created real-time analytical views and implemented an LLM-driven fuzzy search tool.
**The Results: **Increased the speed of market analysis by 40%, provided superior market opportunity insights, and significantly increased conversion rates by improving the core search functionality.
The Challenge: Silos Hiding Market Opportunities
The clientâs primary pain point was a lack of unified truth. Their digital platform generated vast amounts of data, but it was trapped:
- **Siloed Systems: **Inventory was separate from CRM, and Sales data was disconnected from Financials. This made calculating the true cost of customer acquisition or the profitability of specific listings nearly impossible.
- **Poor Market Insight: **Analysts couldnât easily blend internal sales data with external market trends, leading to slow, reactive responses to shifts in property supply and demand.
- **Failing UX: **The most critical tool, the user search bar, was rigid. Common user errors like misspellings, synonyms (âapartmentâ vs. âflatâ), or fuzzy phrases resulted in zero results, prematurely ending the user journey and costing conversions.
The platform was operating as a repository of listings, but not as a true System of Market Intelligence.
Our Solution: A 3-Pillar Data Transformation
Polar Packet implemented a full-stack data transformation, ensuring that the architecture, insights, and user experience were aligned.
Pillar 1: The Foundation (Data Engineering)
The project began with a robust data centralization effort to establish a single source of truth.
- **Data Lakehouse Architecture: **We architected and deployed a Data Lakehouse solution, choosing Snowflake as the primary data platform, utilizing the scalability and flexibility of AWS.
- **Full Centralization: **We built highly resilient pipelines to ingest and standardize data from all mission-critical systems: Inventory, Sales, Financial data, and CRM. This unified data became the single source for everything from accounting to property market analysis.
- **Compliance and Governance: **We ensured the new architecture met all regulatory requirements and established strong governance protocols to secure PII and financial data across all systems.
Pillar 2: Strategic Views (Data Analytics)
Once the data was centralized and reliable, our Data Analytics team built critical views that empowered every department:
- **Engagement Analytics: **Views were created to track detailed user journeys, click-through rates, time-on-page, and property preferences, enabling the UX team to optimize the customer journey.
- **Sales Analytics: **Unified views delivered real-time metrics on sales velocity, pipeline forecasting, and conversion funnel performance across all regions.
- **Property and Market Analysis: **The most powerful views blended internal sales history with external market data, providing analysts with rapid access to metrics on pricing trends, inventory turnover, and market opportunity identification. This slashed market analysis time by 40%.
Pillar 3: User Activation (Data Science & LLMs)
The final, high-value component involved using Data Science to directly improve the user experience and drive conversions.
- **LLM Search Initiative: **We deployed LLM initiatives to enhance the platformâs search functionality. The LLM was trained specifically to understand the property platformâs inventory and user intent, allowing it to interpret fuzzy word searches.
- **Increased Conversions: **When a user misspelled a street name or used a local colloquialism (âpadâ instead of âapartmentâ), the LLM tool correctly interpreted the intent and returned highly relevant property results, eliminating false negative searches. This immediately increased the conversion rate from search query to listing view.
The Results: Better Insights, Higher Conversions
The comprehensive data strategy transformed the client from a data-heavy operation into an agile, intelligent business, providing clear ROI across multiple key metrics:
- **Market Leadership: **Analysts can now rapidly identify market opportunities (e.g., underserved neighborhoods, specific property types seeing high demand) and align inventory acquisition accordingly.
- **Increased User Experience: **The new LLM-powered search bar eliminated a major point of friction, leading to smoother user journeys and a higher success rate in property searches.
- **Conversion Rate Lift: **The increase in search accuracy and user experience directly translated into a lift in conversions from search-to-view and view-to-inquiry.
- **Operational Efficiency: **Finance, Sales, and Inventory teams now operate from a single, trusted source of data, eliminating reporting disputes and saving hundreds of man-hours per month.
Polar Packet provided the end-to-end expertise required to centralize complex enterprise data and deploy a strategic AI solution, cementing the clientâs position as a leader in the digital property market.
About Polar Packet: We specialize in helping tech-forward enterprises solve their most complex data challenges. From building scalable Data Lakehouses on AWS and Snowflake to deploying LLM and Data Science solutions for competitive advantage, we provide the full spectrum of expertise to power your transformation. Contact us today
